1. Field of the Invention
The present invention relates to a turbo decoder and, more particularly, to a turbo decoder which can decrease a time lag, operate at high speed, and hardly deteriorates in characteristics.
2. Description of the Prior Art
A new encoding method called turbo codes which can attain a decoding error rate near the Shannon limit has been proposed by Berrou et al. This method is disclosed in detail in “Proc. IEEE International Conference on Communication (ICC)”, May 1993, pp. 1064–1070.
A characteristic feature of this turbo code decoding is that a code with high decoding complexity is decomposed into elements with low complexity, and the characteristics are sequentially improved by the interaction between the elements. As a decoder for decomposing a code into small elements, a MAP (MAximum Posteriori likelihood) decoder is used, which performs soft-input/soft-output decoding. Although the BCJR (Bahl, Cocke, Jelinek, and Raviv) algorithm is known as a technique for faithfully implementing this MAP decoding, this requires a large calculation amount. As a technique of reducing the calculation amount by approximation, an algorithm such as Max-LogMAP or SOVA is known. Max-LogMAP is designed to approximate the computation process in BCJR with a logarithmic domain. SOVA is designed to obtain soft-input/soft-output data on the basis of the Viterbi algorithm.
Although a characteristic feature of turbo code decoding is that a code with high decoding complexity is decomposed into elements with low complexity, and the characteristics are sequentially improved by the interaction between the elements, it requires iterative operation, and hence it is difficult to realize high-speed operation.
To overcome this drawback, two types of methods may be used. First, in the method shown in FIG. 15, a plurality of turbo decoders each capable of performing N iterations of decoding are made to operate concurrently while being switched by switches; an improvement in average processing throughput can be expected owing to the concurrent processing. As shown in FIG. 15, however, there is a time lag between input operation and output operation. That is, this method is not suited to communication demanding interactive operation. In addition, as shown in FIG. 15, each turbo decoder requires a memory for iterative operation for soft decision data. The ratio of memory operation to overall processing is high, resulting in a large circuit size.
FIG. 16 shows another method. In this method, a plurality of turbo decoders each capable of one iteration of decoding are cascaded to perform pipeline processing. In this case as well, there is a time lag between input operation and output operation, and hence this method is not suited to communication demanding interactive operation. As in the above case, each decoder requires a memory for exchanging soft decision information, resulting in a large circuit size.
Although high-speed operation can be realized by using SOVA designed to perform approximation to obtain soft-input/soft-output data on the basis of the Viterbi algorithm, a deterioration in characteristics occurs due to the approximation.
Services required in next-generation mobile communication systems are classified according to Qos (Quality of service). Time lag is an important factor in a class to which VoIP (Voice over IP) and teleconferences which demand high interactive performance belong.